基于多目标混沌云布谷鸟算法的HAPF优化研究

Chaos Cloud Model Based on Cuckoo Search Algorithm for Multi-objective Optimization Design for Hybrid Active Power Filter

大量非线性电力电子设备的使用给人们的生产生活带来了极大的谐波危害,目前治理谐波的主要手段是投入滤波器。而混合有源滤波器(HAPF)结合了无源滤波器和有源滤波器的特点,是很有前瞻性的滤波系统。HAPF参数优化的算法大多存在收敛精度不高,易陷入局部最优等缺陷。因此,利用混沌云模型多目标布谷鸟搜索算法优化HAPF参数,具有十分重要的工程意义。通过Matlab/Simulink仿真结果对比可知,该算法同粒子群算法(PSO)及原始多目标布谷鸟算法(MOCS)相比,有良好的补偿及效果,成本也有所降低。

The application of a large number of nonlinear power electronic equipment has brought great harm to people＇s production and lives. At present,the filter device is the main way to eliminate harmonics. Hybrid active power filter combines the benefits from power filter and active power filter,so it is proved to be the prospective filter system. Most of the algorithms used for HAPF parameter optimization have some shortcomings such as low convergence precision and local optimization. Therefore,multi-objective optimization is applied to HAPF for the design of parameters,which has very important virtual meaning. Compared with Particle Swarm Optimal algorithm based on multi-objective optimization（MOPSO） and original multi-objective optimization for cuckoo search algorithm（MOCS） in matlab/simulink,this way has an advantage in reactive power compensation and filtering effects,and the cost has been saved.